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检索条件"主题词=Multiclass Object Classification"

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multiclass object classification for Computer Vision using Linear Genetic Programming

Multiclass Object Classification for Computer Vision using L...

引用

24th International Conference Image and Vision Computing New Zealand

作者： Downey, Carlton Zhang, Mengjie Victoria Univ Wellington Sch Engn & Comp Sci Wellington New Zealand

ISBN: (纸本)9781424446971

multiclass classification problems arise naturally in many tasks in computer vision;typical examples include image segmentation and letter recognition. These are among some of the most challenging and important tasks in the area and solutions to them are eagerly sought after. Genetic Programming (GP) is a powerful and flexible machine learning technique that has been successfully applied to many binary classification tasks. However, the traditional form of GP performs poorly on multiclass classification problems. Linear GP (LGP) is an alternative form of GP where programs are represented as sequences of instructions like Java and C++. This paper discusses results which demonstrate the superiority of LGP as a technique for multiclass classification. It also discusses a new extension to LGP which results in a further improvement in the performance on multiclass classification problems.

关键词： AI approaches to computer vision Genetic Programming Linear Genetic Programming multiclass object classification multiclass Image classification

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Daubechies Complex Wavelet Transform based approach for multiclass object classification 3rd

Daubechies Complex Wavelet Transform based approach for Mult...

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3rd International Conference on Control, Automation and Information Sciences (ICCAIS)

作者： Khare, Manish Prakash, Om Srivastava, Rajneesh Kumar Khare, Ashish Univ Allahabad Dept Elect & Commun Allahabad Uttar Pradesh India Univ Allahabad Inst Profess Studies Ctr Comp Educ Allahabad Uttar Pradesh India

ISBN: (纸本)9781479972043

object classification is an important step in different applications such as video surveillance, content based video retrieval etc. The task of multiclass object classification has more challenges. The goal of multi class object classification is to classify objects into one of the chosen classes. In this paper we propose a new method for multiclass object classification which is based on Daubechies complex wavelet transform. Daubechies complex wavelet transform is having advantage of approximate shift invariance and better edge representation as compared to real valued discrete wavelet transform. We have used multiclass support vector machine as a classifier for classification of object. The proposed method has been tested on our own dataset prepared by authors of this paper. Evaluation results shows that the proposed method is better than other state-of-the-art methods and gives better performance for multiclass object classification.

关键词： Daubechies complex wavelet transform (DCxWT) multiclass object classification video surveillance feature selection

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Dual tree complex wavelet transform based multiclass object classification

Dual tree complex wavelet transform based Multiclass Object ...

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12th International Conference on Machine Learning and Applications (ICMLA)

作者： Khare, Ashish Khare, Manish Srivastava, Rajneesh Kumar Univ Allahabad Dept Elect & Commun Image Proc & Comp Vis Lab Allahabad 211002 Uttar Pradesh India

ISBN: (纸本)9780769551449

multiclass object classification is a difficult problem in computer vision application, because of highly variable nature of different objects. The primary goal of this paper is to classify object into one of the chosen classes. The proposed method uses Dual tree complex wavelet transform coefficients as a feature of object. Dual tree complex wavelet transform is having advantage of its better edge representation and approximate shift-invariant property as compared to real valued wavelet transform. We have used multiclass support vector machine classifier for classification of objects. The proposed method has been tested on dataset prepared by authors of this paper. We have tested the proposed method on multiple levels of Dual tree complex wavelet transform. Quantitative evaluation results demonstrate that the proposed method gives better performance for multiclass object classification in comparison to other state-of-the-art methods.

关键词： Dual tree complex wavelet transform multiclass object classification Feature selection

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multiclass object RECOGNITION AND classification USING BOOSTING TECHNIQUE 9

MULTICLASS OBJECT RECOGNITION AND CLASSIFICATION USING BOOST...

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9th International Conference on Computing, Communication and Networking Technologies (ICCCNT)

作者： Singh, Harpreet Gupta, Dinesh Kushwaha, Alok Kumar Singh IKG PTU Kapurthala Dept Comp Sci & Engn Kapurthala Punjab India

ISBN: (纸本)9781538644300

multiclass object classification in a video streams is an ongoing research field in area of computer vision. object classification plays an important role in a wide range of applications such as surveillance, medical and identify unwanted or abandoned objects in public places. Video processing is very challenging process as it requires real time processing and video data is heavy in nature and contains various obstructions. In this paper proposed a machine learning based approach for multiclass object classification. In the proposed approach, Haar-like features and rectangular features are extracted in the integral image representation and then classifier is trained using SAMME (A Stage-wise Additive Modeling using a multiclass Exponential loss function) for multiclass object classification. We have tested our approach successfully in the outdoor environment results on our own data sets. In the experiment results show that the proposed method of multiclass object classification is robust, flexible and efficient.

关键词： multiclass object classification machine learning feature extraction real time processing video stream

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multiclass object RECOGNITION AND classification USING BOOSTING TECHNIQUE

MULTICLASS OBJECT RECOGNITION AND CLASSIFICATION USING BOOST...

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International Conference on Computing, Communication and Networking Technologies

作者： Harpreet Singh Dinesh Gupta Alok Kumar Singh Kushwaha Department of Computer Science and Engineering I.K.G. P.T.U. Kapurthala India

关键词： multiclass object classification Machine learning Feature extraction Real time processing Video stream

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